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Measuring the dynamics of vibrating cables in situ can be challenging using traditional contact-based sensors (e.g., accelerometer). This work proposes a novel computer vision–based technique using a portable unmanned aerial system (UAS) (also referred to as drones) sensing platform to enable the measurement of the dynamic displacements of a cable in a unique blast-loading experiment where other types of sensing may be impractical. The proposed technique utilizes one optical camera equipped on a UAS to record the dynamic displacement of the blast-loaded cable and measure the drift of the UAS as it hovers. Artificial targets attached to the cable are not required because the technique proves effective when tracking natural features inherent in the cable. This makes the proposed technique versatile and convenient for field implementation. This technique also allows simultaneous displacement measurement at multiple points along the cable across the entire field of view of the camera. The natural frequency, damping, and mode shape are successfully identified from the measured cable displacement time histories. Measuring the vibration of a cable is challenging with traditional techniques. A novel technique is proposed to use only one camera attached to a drone to measure the vibration of a cable directly. However, because the drone hovers in the air, there is inherent drift of the drone. The drone's drift is measured with respect to a stationary target using the camera and compensated for to measure the true motion of the cable. To test the proposed technique, a blast was detonated close to the cable to produce vibration in the cable, and the drone hovered above the cable to record its movements. Because the actual movement of the cable is unknown, finite-element simulations were performed to provide a basis for validating the proposed technique. The natural frequency of the finite-element model is compared with that obtained from the measured vibration of the cable. A good agreement was achieved with a 2.1% difference between the simulated and measured natural frequencies. [ABSTRACT FROM AUTHOR]

Lysosomal dysfunction can drive carcinogenesis. Lysosomal‐associated membrane protein 3 (LAMP3), is a member of the Lysosome Associated Membrane Proteins and is involved in the malignant phenotype such as tumour metastasis and drug resistance, while the mechanisms that regulate the malignant progression of tumour remain vague. Our study aims to provide a more systematic and comprehensive understanding of the role of LAMP3 in the progression of various cancers by various databases.We explored the role of LAMP3 in pan‐cancer using The Cancer Genome Atlas (TCGA) and Genotype‐Tissue Expression (GTEx) database. Multiple online web platforms and software were used for data analysis, including HPA, TIMER, TISIDB, GEPIA, UALCAN, Kaplan–Meier plotter, DAVID and TIGER. The immunohistochemistry was used to quantify the LAMP3 and PD‐L1 expression levels in cancer.High LAMP3 expression was found in most cancers and differentially expressed across molecular and immune subtypes. The expression of LAMP3 was involved in the immune‐associated processes of Antigen processing and presentation, Th17 cell differentiation, Th1 and Th2 cell differentiation, and the immune‐associated pathways of T cell receptor and B cell receptor signalling pathways in most cancers. It also correlated with genetic markers of immunomodulators in various cancers. LAMP3 and PD‐L1 expression in BRCA and HNSC tissues was higher than that in corresponding adjacent normal tissues by immunohistochemistry. There is a significant correlation between the expression of LAMP3 and PD‐L1.Our study elucidates that LAMP3 has different expression patterns and genetic alteration patterns in different tumours. It is a potential biomarker for immune‐related cancer diagnosis, prognosis and efficacy prediction. [ABSTRACT FROM AUTHOR]

The effect and the mechanism of high glucose on fish muscle cells are not fully understood. In the present study, muscle cells of olive flounder (Paralichthys olivaceus) were treated with high glucose (33 mM) in vitro. Cells were incubated in three kinds of medium containing 5 mM glucose, 5 mM glucose and 28 mM mannitol (as an isotonic contrast) or 33 mM glucose named the Control group, the Mannitol group and the high glucose (HG) group, respectively. Results showed that high glucose increased the ADP:ATP ratio and the reactive oxygen species (ROS) level, decreased mitochondrial membrane potential (MMP), induced the release of cytochrome C (CytC) and cell apoptosis. High glucose also led to cell glycogen accumulation by increasing the glucose uptake ability and affecting the mRNA expressions of glycogen synthase and glycogen phosphorylase. Meanwhile, it activated AMP-activated protein kinase (AMPK), inhibited the activity of mammalian target of rapamycin (mTOR) signalling pathway and the expressions of myogenic regulatory factors (MRF). The expressions of myostatin-1 (mstn-1) and E3 ubiquitin ligases including muscle RING-finger protein 1 (murf-1) and muscle atrophy F-box protein (mafbx) were also increased by the high glucose treatment. No difference was found between the Mannitol group and the Control group. These results demonstrate that high glucose has the effects of inducing apoptosis, increasing glycogen accumulation and inhibiting protein synthesis on muscle cells of olive flounder. The mitochondria-mediated apoptotic signalling pathway, AMPK and mTOR pathways participated in these biological effects. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of matching vehicles across multiple sightings under variations in illumination and camera poses. Since multiple observations of a vehicle are separated in large temporal and/or spatial gaps, thus prohibiting the use of standard frame-to-frame data association, we employ features extracted over a sequence during one time interval as a vehicle fingerprint that is used to compute the likelihood that two or more sequence observations are from the same or different vehicles. Furthermore, since our domain is aerial video tracking, in order to deal with poor image quality and large resolution and quality variations, our approach employs robust alignment and match measures for different stages of vehicle matching. Most notably, we employ a heterogeneous collection of features such as lines, points, and regions in an integrated matching framework. Heterogeneous features are shown to be important. Line and point features provide accurate localization and are employed for robust alignment across disparate views. The challenges of change in pose, aspect, and appearances across two disparate observations are handled by combining a novel feature-based quasi-rigid alignment with flexible matching between two or more sequences. However, since lines and points are relatively sparse, they are not adequate to delineate the object and provide a comprehensive matching set that covers the complete object. Region features provide a high degree of coverage and are employed for continuous frames to provide a delineation of the vehicle region for subsequent generation of a match measure. Our approach reliably delineates objects by representing regions as robust blob features and matching multiple regions to multiple regions using Earth Mover's Distance (EMD). Extensive experimentation under a variety of real-world scenarios and over hundreds of thousands of Confirmatory Identification (CID) trails has demonstrated about 95 percent accuracy in vehicle reacquisition with both visible and Infrared (IR) imaging cameras. Index Terms--Video object tracking and reacquisition, object matching, feature matching, image alignment and matching.